A selection of posts showcasing my work
In this course, I completed course material on control flow, lists, loops, functions, strings, modules, dictionaries, files, and classes. Now that I have learned some Python basics, next I will learn how to use Python within QGIS.
This is the way to Hanoi by backroads (excluding large highways, and prioritizing small roads over big roads)
I am located in Thai Nguyen city, which is about 80 km North of the Hanoi. The way to get to Hanoi is usually by bus, which travels on the motorway (aka freeway). I wanted to know if I can go to Hanoi on a bicycle, taking the back roads. The goal of this project was to find the optimal route to take by bicycle, with the priority being smaller roads.
I know that I don’t want to ride my bicycle on the major highways at all, so I don’t need to include them in my road network. I downloaded from OSM only the highways in the smallest 3 classes.
I prefer smaller roads, even if it means going a slightly greater distance. I want the tool to find the route that takes the smallest roads as much as possible.
Unclassified roads → Most preferred
Tertiary roads → Second priority
Secondary roads → Least preferred
To do this, I basically tell it, ‘smaller roads are faster, bigger roads are slower’. Then I tell it, ‘go find the fastest route’, and so it finds the route with more small roads.
In the attribute table of the highway layer, I used the field calculator to create a new field called ‘speed’. I calculated it as follows:
CASE
WHEN "highway" IN ('unclassified', 'unclassified_link') THEN 30
WHEN "highway" IN ('tertiary', 'tertiary_link') THEN 20
WHEN "highway" IN ('secondary', 'secondary_link') THEN 10
ENDI then ran the Shortest Path tool in QGIS with the “Fastest Path” option and the new attribute selected for the “Speed Field”. Since the tool prioritizes higher speeds, roads with higher values in the new field are preferred. The resulting output is more Tertiary highway than anything else.
Finally, to view the route on my mobile phone while out cycling, I imported the route to Google my maps. Thanks to my phone’s GPS, I can see my location as a blue dot.
Description: A planting layout for a sustainable agriculture model inspired by the environmental conditions of Central New Mexico. Design priorities are drought tolerance, commercial yield and ecological design. The row sequence is A-B-C-B-A where row A is honey mesquite with four-wing saltbush, row B is prickly pear cactus and row C is desert wildflowers. The rows are parallel to the general direction of the contour.
Following a tutorial, I identified suitable areas for development which are far from water, near to roads and not in a protected region.
Tutorial: Multi Criteria Overlay Analysis (QGIS3) — QGIS Tutorials and Tips
This map was begun by following a tutorial, then extended. The tutorial was to use a change assessment dataset to identify urban growth patterns in the city of Johannesburg from 2014 to 2018. Once done, I added OSM features including major highways and rails. I calculated the raster area for the 3 classes and added a pie chart. Finally, I designed the print layout.
For this project I first followed a tutorial, then added to it by visualizing the result in a different way. The tutorial involved using the spatial join with summary algorithm to join the average street rating to each borough. I decided to use graduated symbology by the value of the pavement rating for both the boroughs and the individual streets to make a more effective thematic map.
Tutorial: Performing Spatial Joins (QGIS3) — QGIS Tutorials and Tips
Description: This is work done under Matt Wilson, the then-sustainable agriculture person at the Berea College farm. The project was to create a perennial polyculture system for livestock on 1 acre of Berea College farmland. These screenshots from Sketchup show contours I was able to create using elevation data I had obtained from Google Earth. The idea for the design was chestnut, apple, mulberry and swamp oak planted on contour. The species were selected based partly on USGS soil data, which is shown.
Description: This thematic map shows rice paddy yield of the 63 provinces of Vietnam. The map makes it easy to identify the regions with the highest yield. As expected, the Red River delta and the Mekong River deltas are among the highest yield regions.
Data: provided by the general statistics office website of the Vietnamese government.
Tools: QGIS
Twice a week, participants meet in Zoom to practice English. The meetings involve small group discussions in breakout rooms where the participants speak with each other about a discussion prompt. Conversations last 5 minutes and involve 2-4 students. Over the course of about 8 months in 2023, there was a total of 278 separate small group conversations involving 52 participants from 21 different provinces across 2 countries. The meetings are free and open, so attendance varies by location as people find the class on their own or are invited by friends. However, most participants are in Vietnam due to efforts early on to advertise in Vietnam, and also the design of the class and content being made to suit a Vietnamese audience.
Description: Shows the change over a 10-year period in the built-up area within the municipal boundary of Thai Nguyen city, Vietnam.
Data: Landsat 8 images
Tools: QGIS, Semi-automatic Classification Plugin